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World Rank of a
University
Rohit Kamat
May 13, 2016
SDS 358
Introduction
Objectives: Investigate the significance of greater proportion
of variance on Alumni Score and Awards Score have on the
total score for determining the world rank of a university, when
controlling for Nature and Science Score and PUB Score.
Since I was a Junior in high school, I have been curious on
what factors caused certain universities to be ranked higher
than others.
Hypotheses: Alumni and Award score does account for a
significant greater proportion of variance for determining the world
rank of a university when controlling for Nature and Science Score
and PUB Score.
Methods
Sample: Subjects were the top 100 World Universities from
each year from 2005 to 2015. The total score of universities
(quantitative), alumni score (quantitative), award score
(quantitative), nature and science score (quantitative), and
PUB score (quantitative) were measured. After tagging the
observation that I will use for the model, I had 1101 samples.
From using the three outs method, I had 18 outliers that were
removed.
Analysis Method: A sequential multiple regression was
performed.
Descriptives
Response Variable:
Mean SD Min Max
Total Score 36.38 13.56 23.5 100
Explanatory Variables:
Mean SD Min Max
NS Score
(Control Variable)
16.08 12.51 0 100
PUB Score
(Control Variable)
38.25 13.05 7.3 100
Alumni Score 9.16 14.14 0 100
Award Score 7.69 15.49 0 100
Results
Overall Significance of Variance Change:
Model RSS Df F-value P-value
Control Variables 24598.20
+ Variables of Interest 2892.30 2 4045.1 <.001
Regression Table:
Model 1 (Just Control Variables):
Coefficient Estimate SE t-value P-value
Intercept 5.32279 .66173 8.044 <.001
NS 0.76845 .01287 59.073 <.001
PUB 0.10881 .01541 7.062 <.001
Overall Model Fit: F(2,1080)= 3544, p<.001; Multiple R2
= 0.8678, Adjusted R2
=0.8675
Model 2 (With Variable of Interest)
Overall Model Fit: F(4,1078) = 1.074 * 104
, p < 0.001; Multiple R2
= 0.9845, Adjusted R2
= 0.9844
Difference of Variance between Variables of Interest and Control
Variables: 0.1166785
Coefficient Estimate SE t-value P-value
Intercept 1.244374 .238944 5.208 <.001
NS .410574 .006180 66.436 <.001
PUB .24210 .005943 40.741 <.001
Alumni .109702 .004260 25.753 <.001
Award .218962 .004365 50.166 <.001
0 200 400 600 800 1000
0.0000.0050.0100.0150.020
Cook's Distance
Index
Cook'sDistance
Assumptions
Assumptions: To check for multicollinearity I used the Variation
Inflation Factor (VIF). The Variance Inflation Factor for all variables was
under 5, so there was no multicollinearity in the model. A Residual vs.
Fitted Plot was used to check and confirmed Homoscedasticity. Cook’s
Distance Plot and the use of Three Outs was used to determine outlier
removal.
Discussion
Interpretation: The variance change from the first model to the
second model was significant with F(2,1078)= 4045.1, p<.05. Difference of
variance between the variable of interest and the control variables is
0.1166785. The overall full model (second model) was significant with
F(4,1078)= 1 * 104
, p<.05. The individual slopes of the full model showed a
positive impact on the total score of a university ranking for NS Score
(=0.410574, t(1078)=66.436, p<.05), PUB Score (=0.242120,
t(1078)=40.741, p<.05), Alumni Score (=0.109702, t(1078)=25.743,
p<.05), Award Score (=0.218962, t(1078)=50.166, p<.05).
Limitations: The model did not take into account other
factors that impact the total score of a university such as the
HiCi Score and the PCP score.
Implications: Several indicators for determining the rank of a
university were based on research, papers published and
awards based on staff members and alumni from the
institution. I think factors related to the students such as
employment of graduates, quality of professors, value of
degree from the school in terms of income, graduation rate
should also determine the rank of the university.
References: The methodology and use of the Academic
Ranking of World University website.
http://www.shanghairanking.com/

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World Rank of a University

  • 1. World Rank of a University Rohit Kamat May 13, 2016 SDS 358
  • 2. Introduction Objectives: Investigate the significance of greater proportion of variance on Alumni Score and Awards Score have on the total score for determining the world rank of a university, when controlling for Nature and Science Score and PUB Score. Since I was a Junior in high school, I have been curious on what factors caused certain universities to be ranked higher than others. Hypotheses: Alumni and Award score does account for a significant greater proportion of variance for determining the world rank of a university when controlling for Nature and Science Score and PUB Score.
  • 3. Methods Sample: Subjects were the top 100 World Universities from each year from 2005 to 2015. The total score of universities (quantitative), alumni score (quantitative), award score (quantitative), nature and science score (quantitative), and PUB score (quantitative) were measured. After tagging the observation that I will use for the model, I had 1101 samples. From using the three outs method, I had 18 outliers that were removed. Analysis Method: A sequential multiple regression was performed.
  • 4. Descriptives Response Variable: Mean SD Min Max Total Score 36.38 13.56 23.5 100 Explanatory Variables: Mean SD Min Max NS Score (Control Variable) 16.08 12.51 0 100 PUB Score (Control Variable) 38.25 13.05 7.3 100 Alumni Score 9.16 14.14 0 100 Award Score 7.69 15.49 0 100
  • 5. Results Overall Significance of Variance Change: Model RSS Df F-value P-value Control Variables 24598.20 + Variables of Interest 2892.30 2 4045.1 <.001 Regression Table: Model 1 (Just Control Variables): Coefficient Estimate SE t-value P-value Intercept 5.32279 .66173 8.044 <.001 NS 0.76845 .01287 59.073 <.001 PUB 0.10881 .01541 7.062 <.001 Overall Model Fit: F(2,1080)= 3544, p<.001; Multiple R2 = 0.8678, Adjusted R2 =0.8675
  • 6. Model 2 (With Variable of Interest) Overall Model Fit: F(4,1078) = 1.074 * 104 , p < 0.001; Multiple R2 = 0.9845, Adjusted R2 = 0.9844 Difference of Variance between Variables of Interest and Control Variables: 0.1166785 Coefficient Estimate SE t-value P-value Intercept 1.244374 .238944 5.208 <.001 NS .410574 .006180 66.436 <.001 PUB .24210 .005943 40.741 <.001 Alumni .109702 .004260 25.753 <.001 Award .218962 .004365 50.166 <.001
  • 7. 0 200 400 600 800 1000 0.0000.0050.0100.0150.020 Cook's Distance Index Cook'sDistance Assumptions Assumptions: To check for multicollinearity I used the Variation Inflation Factor (VIF). The Variance Inflation Factor for all variables was under 5, so there was no multicollinearity in the model. A Residual vs. Fitted Plot was used to check and confirmed Homoscedasticity. Cook’s Distance Plot and the use of Three Outs was used to determine outlier removal.
  • 8. Discussion Interpretation: The variance change from the first model to the second model was significant with F(2,1078)= 4045.1, p<.05. Difference of variance between the variable of interest and the control variables is 0.1166785. The overall full model (second model) was significant with F(4,1078)= 1 * 104 , p<.05. The individual slopes of the full model showed a positive impact on the total score of a university ranking for NS Score (=0.410574, t(1078)=66.436, p<.05), PUB Score (=0.242120, t(1078)=40.741, p<.05), Alumni Score (=0.109702, t(1078)=25.743, p<.05), Award Score (=0.218962, t(1078)=50.166, p<.05). Limitations: The model did not take into account other factors that impact the total score of a university such as the HiCi Score and the PCP score.
  • 9. Implications: Several indicators for determining the rank of a university were based on research, papers published and awards based on staff members and alumni from the institution. I think factors related to the students such as employment of graduates, quality of professors, value of degree from the school in terms of income, graduation rate should also determine the rank of the university. References: The methodology and use of the Academic Ranking of World University website. http://www.shanghairanking.com/